Director, Data Scientist, Global Payment Network

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Riverwoods, ILMcLean, VAChicago, ILNew York, NY
Employment: Full-time
Posted: 5 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $228k

$175k most similar roles pay here $274k

This listing doesn't post a salary. Most similar roles pay $192,050–$264,000.

Based on 240 similar postings.

Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 1743 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 947 roles with salary data.

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At a glance

TL;DR · Director, Data Scientist, Global Payment Network

Role Posting Log in to save

Director, Data Scientist - Global Payment Network joins the Global Payment Network Data Solutions and Modeling team to build machine learning and AI agents that drive scalable intelligence across the payments ecosystem. This role involves collaborating with cross-functional teams of data scientists, software engineers, and product managers to develop models for fraud, risk, merchant acceptance, and monitoring. The successful candidate will manage all phases of model development, from design through training, evaluation, validation, and implementation. To uncover insights within large volumes of numeric and textual data, the role utilizes a technical stack including Python, Conda, AWS, H2O, Spark, Scala, R, and relational databases. This position addresses complex problems in the payments sector by creating automated tools to support merchant intelligence and provide foundational capabilities for smarter business decisions across the global payment network.

Skills

Python Machine Learning AWS Spark H2O Conda Relational Databases Scala R Data Analysis Cloud Computing

What you'll do

Build machine learning models through all phases of development including design, training, evaluation, validation, and implementation.
Use Python, Spark, H2O, and AWS to extract insights from large volumes of numeric and textual data.
Develop AI agents and machine learning tools to support fraud risk, merchant acceptance, and monitoring.
Translate complex technical findings into tangible business goals for stakeholders.
Research and evaluate emerging technologies to improve existing data science solutions.
Define and solve large, ambiguous problems within the payments ecosystem.
Manage and develop talent across the data science team.

What we're looking for

A Bachelor's degree in a quantitative field plus 9 years of experience performing data analytics.
A Master's degree in a quantitative field or an MBA with a quantitative concentration plus 7 years of experience performing data analytics.
A PhD in a quantitative field plus 4 years of experience performing data analytics.
At least 4 years of experience leveraging open source programming languages for large scale data analysis.
At least 4 years of experience working with machine learning.
At least 4 years of experience utilizing relational databases.
Extensive multi-project experience leading data science solutions within payments, financial services, or fintech sectors (preferred).
Experience with AWS, managing people, and using Python, Scala, or R for large scale data analysis (preferred).

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